Methodological Issues in the Clinical Validation of Biomarkers for Alzheimer's Disease: The Paradigmatic Example of CSF

Artificial intelligence for biomarker discovery in Alzheimer's disease and dementia

With the increase in large multimodal cohorts and high-throughput technologies, the potential for discovering novel biomarkers is no longer limited by data set size. Artificial intelligence (AI) and machine learning approaches have been developed to detect novel biomarkers and interactions in complex data sets. We discuss exemplar uses and evaluate current applications and limitations of AI to discover novel biomarkers. Remaining challenges include a lack of diversity in the data sets available, the sheer complexity of investigating interactions, the invasiveness and cost of some biomarkers, and poor reporting in some studies. Overcoming these challenges will involve collecting data from underrepresented populations, developing more powerful AI approaches, validating the use of noninvasive biomarkers, and adhering to reporting guidelines. By harnessing rich multimodal data through AI approaches and international collaborative innovation, we are well positioned to identify clinically useful biomarkers that are accurate, generalizable, unbiased, and acceptable in clinical practice. HIGHLIGHTS: Artificial intelligence and machine learning approaches may accelerate dementia biomarker discovery. Remaining challenges include data set suitability due to size and bias in cohort selection. Multimodal data, diverse data sets, improved machine learning approaches, real-world validation, and interdisciplinary collaboration are required.

Validating blood tests as a possible routine diagnostic assay of Alzheimer's disease

INTRODUCTION

In recent years, exciting developments in disease modifying treatments for Alzheimer's disease (AD) have made accurate and timely diagnosis of this disease a priority. Blood biomarkers (BBMs) for amyloid pathology using improved immunoassay and mass spectrometry techniques have been an area of intense research for the last 10 years and are coming to the fore, as a real prospect to be used in the clinical diagnostics of the disease.

AREAS COVERED

The following review will update and discuss blood biomarkers that will be most useful in diagnosing AD and the context necessary for their implementation.

EXPERT OPINION

It is clear we now have BBMs, and technology to measure them, that are capable of detecting amyloid pathology in AD. The challenge is to validate them across platforms and populations to incorporate them into clinical practice. It is important that implementation comes with education, we need to give clinicians the tools for appropriate use and interpretation. It is feasible that BBMs will be used to screen populations, initially for clinical trial entry but also therapeutic intervention in the foreseeable future. We now need to focus BBM research on other pathologies to ensure we accelerate the development of therapeutics for all neurodegenerative diseases.

Lights and Shadows of Cerebrospinal Fluid Biomarkers in the Current Alzheimer's Disease Framework

BACKGROUND

The most significant biomarkers that are included in the Alzheimer's disease (AD) research framework are amyloid-β plaques deposition, p-tau, t-tau, and neurodegeneration.Although cerebrospinal fluid (CSF) biomarkers are included in the most recent AD research criteria, their use is increasing in the routine clinical practice and is applied also to the preclinical phases of AD, including mild cognitive impairment. The role of these biomarkers is still unclear concerning the preclinical stage of AD diagnosis, the CSF methodology, and the costs-benefits of the biomarkers' tests. The controversies regarding the use of biomarkers in the clinical practice are related to the concepts of analytical validity, clinical validity, and clinical utility and to the question of whether they are able to diagnose AD without the support of AD clinical phenotypes.

OBJECTIVE

The objective of the present work is to expose the strengths and weaknesses of the use of CSF biomarkers in the diagnosis of AD in a clinical context.

METHODS

We used PubMed as main source for articles published and the final reference list was generated on the basis of relevance to the topics covered in this work.

RESULTS

The use of CSF biomarkers for AD diagnosis is certainly important but its indication in routine clinical practice, especially for prodromal conditions, needs to be regulated and also contextualized considering the variety of possible clinical AD phenotypes.

CONCLUSION

We suggest that the diagnosis of AD should be understood both as clinical and pathological.

Application of Near-Infrared Spectroscopy for Evidence-Based Psychotherapy

This perspective article discusses the importance of evidence-based psychotherapy and highlights the usefulness of near-infrared spectroscopy (NIRS) in assessing the effects of psychotherapeutic interventions as a future direction of clinical psychology. NIRS is a safe and non-invasive neuroimaging technique that can be implemented in a clinical setting to measure brain activity via a simple procedure. This article discusses the possible benefits and challenges of applying NIRS for this purpose, and the available methodology based on previous studies that used NIRS to evaluate psychotherapeutic effects. Furthermore, this perspective article suggests alternative methodologies that may be useful, namely, the single- and multi-session evaluations using immediate pre- and post-intervention measurements. These methods can be used to evaluate state changes in brain activity, which can be derived from a single session of psychotherapeutic interventions. This article provides a conceptual schema important in actualizing NIRS application for evidence-base psychotherapy.

Clinically oriented Alzheimer's biosensors: expanding the horizons towards point-of-care diagnostics and beyond

The development of minimally invasive and easy-to-use sensor devices is of current interest for ultrasensitive detection and signal recognition of Alzheimer's disease (AD) biomarkers. Over the years, tremendous effort has been made on diagnostic platforms specifically targeting neurological markers for AD in order to replace the conventional, laborious, and invasive sampling-based approaches. However, the sophistication of analytical outcomes, marker inaccessibility, and material validity strongly limit the current strategies towards effectively predicting AD. Recently, with the promising progress in biosensor technology, the realization of a clinically applicable sensing platform has become a potential option to enable early diagnosis of AD and other neurodegenerative diseases. In this review, various types of biosensors, which include electrochemical, fluorescent, plasmonic, photoelectrochemical, and field-effect transistor (FET)-based sensor configurations, with better clinical applicability and analytical performance towards AD are highlighted. Moreover, the feasibility of these sensors to achieve point-of-care (POC) diagnosis is also discussed. Furthermore, by grafting nanoscale materials into biosensor architecture, the remarkable enhancement in durability, functionality, and analytical outcome of sensor devices is presented. Finally, future perspectives on further translational and commercialization pathways of clinically driven biosensor devices for AD are discussed and summarized.

Nanomedicine-based technologies and novel biomarkers for the diagnosis and treatment of Alzheimer's disease: from current to future challenges

Increasing life expectancy has led to an aging population, which has consequently increased the prevalence of dementia. Alzheimer's disease (AD), the most common form of dementia worldwide, is estimated to make up 50-80% of all cases. AD cases are expected to reach 131 million by 2050, and this increasing prevalence will critically burden economies and health systems in the next decades. There is currently no treatment that can stop or reverse disease progression. In addition, the late diagnosis of AD constitutes a major obstacle to effective disease management. Therefore, improved diagnostic tools and new treatments for AD are urgently needed. In this review, we investigate and describe both well-established and recently discovered AD biomarkers that could potentially be used to detect AD at early stages and allow the monitoring of disease progression. Proteins such as NfL, MMPs, p-tau217, YKL-40, SNAP-25, VCAM-1, and Ng / BACE are some of the most promising biomarkers because of their successful use as diagnostic tools. In addition, we explore the most recent molecular strategies for an AD therapeutic approach and nanomedicine-based technologies, used to both target drugs to the brain and serve as devices for tracking disease progression diagnostic biomarkers. State-of-the-art nanoparticles, such as polymeric, lipid, and metal-based, are being widely investigated for their potential to improve the effectiveness of both conventional drugs and novel compounds for treating AD. The most recent studies on these nanodevices are deeply explained and discussed in this review.

Use of Biomarkers in Ongoing Research Protocols on Alzheimer's Disease

The present study aimed to describe and discuss the state of the art of biomarker use in ongoing Alzheimer’s disease (AD) research. A review of 222 ongoing phase 1, 2, 3, and 4 protocols registered in the clinicaltrials.gov database was performed. All the trials (i) enrolling subjects with clinical disturbances and/or preclinical diagnoses falling within the AD continuum; and (ii) testing the efficacy and/or safety/tolerability of a therapeutic intervention, were analyzed. The use of biomarkers of amyloid deposition, tau pathology, and neurodegeneration among the eligibility criteria and/or study outcomes was assessed. Overall, 58.2% of ongoing interventional studies on AD adopt candidate biomarkers. They are mostly adopted by studies at the preliminary stages of the drug development process to explore the safety profile of novel therapies, and to provide evidence of target engagement and disease-modifying properties. The biologically supported selection of participants is mostly based on biomarkers of amyloid deposition, whereas the use of biomarkers as study outcomes mostly relies on markers of neurodegeneration. Biomarkers play an important role in the design and conduction of research protocols targeting AD. Nevertheless, their clinical validity, utility, and cost-effectiveness in the “real world” remain to be clarified.